shantoroy

import getpass
import paramiko
import time

def execute_command_ssh(olt_ip, username, password):
    try:
        # Create an SSH client instance
        ssh_client = paramiko.SSHClient()

        # Automatically add the server's host key

shantoroy

#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File    :   splitwise_personal_cost_analytics.py
@Time    :   2023/03/09 13:08:34
@Version :   1.0
@Contact :   sroy10@uh.edu
@Desc    :   Splitwise Class for analyzing and visualizing personal expenditure
'''

shantoroy

#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File    :   custom_api.py
@Time    :   2023/04/09 17:01:04
@Author  :   NSL
@Version :   1.0
@Contact :   sroy10@uh.edu
@Desc    :   None
'''

shantoroy

Cloud Tool	Local Alternative
Google Docs	Microsoft Word
Google Slides	Microsoft PowerPoint
Google Sheets	Microsoft Excel
Trello	Asana
Zoom	Skype
Slack	Microsoft Teams
GitHub	Git
Canva	Adobe Photoshop

shantoroy

#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File    :   redaction.py
@Time    :   2023/02/09 20:57:22
@Author  :   Shanto Roy 
@Version :   1.0
@Contact :   sroy10@uh.edu
@License :   (C)Copyright 2020-2021, Shanto Roy
@Desc    :   Class that replace real information with fake believable ones.

shantoroy

# Helps Visualizing overall summary of all features in a dataset

# !pip install numpy
# !pip install pandas
# !pip install autoviz
# !pip install xlrd
# !pip install xgboost

from autoviz.AutoViz_Class import AutoViz_Class
AV = AutoViz_Class()

shantoroy

# Modified from source: https://machinelearningmastery.com/feature-selection-machine-learning-python/

# Feature Selection with Univariate Statistical Tests
from pandas import read_csv
from numpy import set_printoptions
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_classif
from sklearn.feature_selection import chi2

shantoroy

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import classification_report, confusion_matrix
import joblib
import os


def preprocess(dataset, x_iloc_list, y_iloc, testSize):

shantoroy

// source: https://stackoverflow.com/questions/43849847/executing-shellcode-in-shared-memory-with-mmap

#include <string.h>
#include <sys/mman.h>

// /bin/sh shellcode
const char shellcode[] = "\x01\x30\x8f\xe2\x13\xff\x2f\xe1\x03\xa0\x52\x40\xc2\x71\x05\xb4\x69\x46\x0b\x27\x01\xdf\x2d\x1c\x2f\x62\x69\x6e\x2f\x73\x68\x58";

int main(int argc, char **argv)
{

shantoroy

// Function Pointer 

#include <stdio.h>

int sum(int a, int b)
{
    return a+b;
}

void hello_name(char *name)